I compaired two song of the corpus using chordograms. The first chordogram is a visualization of 'My Reverie' by Ella Fitzgerald. This song contains some clear repetitions. The second chrodogram is a visualization of the clasical song that inspired Ella Fitzgerald, named 'Rêverie' by Claude Debussy. An interesting observation is that have some clear similarities. Although Debussy's Rêverie is bit more stretched out, you can spot the same pattern. This is also something that you can hear back if you listen to the two songs. The lighter/yelllowe parts in the middle and in the end are in both pieces audible. Both the songs sound louder, but in a different way. In Fitzgerald's song increases sound her voice and in Debussy's song increases the sound of the instruments.
The self-similarity matrices are an interesting tool for this corpus. By making to similarity matrices you can compair the song that is inspired by classical songs and the classicals songs itself. I did this for the songs 'all by myself' - Eric Carmen and the song that is it's source of inspiration 'Piano Concerto No. 2 in C minor' - Sergei Rachmaninoff. You can see that the similiarity matrices do correspond and that the patterns look like each other. That looks like they have the same repetitions. 'All by myself' is a song in the corpus that has clear influences of Piano Concerto No. 2 in C minor. So that explains why the two self-similarity matrices look like each other.
and I really liked it. It is a disco instrumental song based on Beethoven's Symphony No. 5.
I thought using famous classical music pieces to create new songs of another genre is a really cool concept. So I did some research and discovered that there are many more famous songs that are based
and inspired on a classical piece of music, also songs I know for a long time
but never knew that they have a classical origin.
My corpus includes classical pieces and their linked new songs.
I have found 25 pairs, so 50 songs in total.
I think that this corpus makes really interesting comparisments possible, on different levels.
For example between the songs based on the classical songs.
What are the differences and similarities between these songs?
Is the classical input used in the same way? Is there an common genre?
But of course exploring relation between the song based on a classic song and the original classical song itself is really interesting.
To what extent do you see the original classical back in the new songs? In which way is the original song adapted in de new song? Which changes are made? Maybe the tempo changed or other instruments are used.
There are pairs of tracks in the corpus, like 'I can' – Nas/'Für Elise' -Beethoven and 'A fifth of Beethoven'-Woody/ Beethoven's Fifth Symphony- Beethoven,
in which the relation with the origin classical song is very obvious. But there are also pairs in the corpus in which the original songs are more subtly included, like 'Grace Kelly'- Mika / 'Largo Al Factotum'- Rossini.
It's important that I define my research a bit more, but I think this is a really interesting and fun corpus to explore with enough possibilities.
songs in the corpus
| New | Classical |
|---|---|
| I can - Nas | Fur Elise - Beethoven |
| A fifth of Beethoven - Walter Murphy | Symphony No, 5 in C minor - Beethoven |
| Because - The Beatles | Sonata No. 14 "Moonlight" in C sharp |
| Can't Help falling in Love - Elvis Presley | Martini: Plaisir d'amour - Jean-Paul-Egide Martini |
| All by myself - Eric Carmen | Piano Concerto No. 2 in C minor - Sergei Rachmaninoff |
| The Globalist - Muse | Nimord From Enigma Variations - Edward Elgar |
| Say You'll Go | Clair de Lune, L.32 - Claude Debussy |
| Old money - Lana Del Rey | A time for Us - Nino Rota, Angele Dubeau |
| Little Me - Little Mix | Pavane, Op. 50 - Gabriel Faure |
| I Believe in Father Christmas - Greg Lake | Prokofiev: suite from lieutenant kijé - Sergei Prokofiev |
| Road to Joy - Bright Eyes | Symphony No. 9 in D Minor, Op. 125 - Ludwig van Beethoven |
| It's A Hard Life - Queen | Vesti la giubba - Ruggero Leoncavallo |
| Tocacata - Sky | Toccata and Fugue in D minor - Johann Sebastian Bach |
| A Whiter Shade of Pale - Procol Harum | Air on a G string - Johann Sebastian |
| Could it Be Magic - Barry Manilow | Preludes, Op. 28: No 20 in C minor - Frederic Chopin |
| Go West - Pet Shop Boys | Canon in D - Johann Pachelbel |
| Alejandro - Lady Gaga | Csardas - Vittorio Monti |
| Ave Maria - Beyonce | Schubert: Ave Maria, D. 839 - Franz Schubert |
| Sara - Starship | Fantasia on a Theme by Thomas Tallis - Ralph Vaughan Williams |
| Grace Kelly - MIKA | Largo al factotum - Gioachino Rossini |
| Exit Music (For a Film) - Radiohead | Prelude in E minor, Op. 28, No. 4 - Frederic Chopin |
| Bad Romance - Lady Gaga | The Well-Tempered Clavier: Book 1 - Johann Sebastian Bach |
| Russians - Sting | Lieutenant Kijé, Opt. 60: 2. Romance - Sergei Prokofiev |
| My Reverie - Ella Fitzgerald | Reverie - Claude Debussy |
| Hey Jude - The Beatles | Arioso (Adagio in G) - Johann Sebatian Bach |
I made some simple but clear histograms of the loudness and danceability of the classical en new songs, In the histograms you see the clear diference in the distributions of the two categories, classical songs and the new songs that are basted on the classical songs. The new songs are signifant louder than the classical songs. The danceability is also higher for the new songs.
This plot shows 4 variables. The x-axis variance, the y-axis energy, the size of the dots is loudness and the color is the mode.It points out some difference between the classical songs and the newer songs. Especially the difference in Valence and the difference energy are remarkable.
compmus_long_distance(
because %>% mutate(pitches = map(pitches, compmus_normalise, "manhattan")),
sonata %>% mutate(pitches = map(pitches, compmus_normalise, "manhattan")),
feature = pitches,
method = "manhattan"
) %>%
ggplot(
aes(
x = xstart + xduration / 2,
width = xduration,
y = ystart + yduration / 2,
height = yduration,
fill = d
)
) +
geom_tile() +
coord_equal() +
labs(x = "because", y = "sonata") +
theme_minimal() +
scale_fill_viridis_c(guide = NULL)all <-
get_tidy_audio_analysis("4rrrn8OLrttq7r9RgNXalU") %>% # Change URI.
compmus_align(bars, segments) %>% # Change `bars`
select(bars) %>% # in all three
unnest(bars) %>% # of these lines.
mutate(
pitches =
map(segments,
compmus_summarise, pitches,
method = "rms", norm = "euclidean" # Change summary & norm.
)
) %>%
mutate(
timbre =
map(segments,
compmus_summarise, timbre,
method = "rms", norm = "euclidean" # Change summary & norm.
)
)wood %>%
mutate(pitches = map(pitches, compmus_normalise, "euclidean")) %>%
compmus_gather_chroma() %>%
ggplot(
aes(
x = start + duration / 2,
width = duration,
y = pitch_class,
fill = value
)
) +
geom_tile() +
labs(x = "Time (s)", y = NULL, fill = "Magnitude") +
theme_minimal() +
scale_fill_viridis_c()